On Thu, 24 Apr 2008, Abhilash Venu wrote:
> Hi Gordon,
>
> I am a experimentalist, but not with great statistical knowledge and
R
> experiance. Recently we started doing single color experiments using
Agilent
> array.
> I think that we does not have any specific function to read the
single
> channel data, But as once you suggested I used the dummy values for
'R' and
> 'Rb' and performed furhter normalization by the following commands.
>> txt_files <- dir(pattern=".txt")
This will read files in alphabetical order. Will this agree with your
design matrix? You can specify the order of the files using a targets
file.
>> RG<-read.maimages(txt_files, columns = list(G = "gMeanSignal", Gb =
> "gBGMeanSignal",
> R="gMedianSignal",Rb="gBGMedianSignal"),
> annotation= c("Row", "Col",
> "ProbeUID","ProbeName", "GeneName",))
>> Rgene<-backgroundCorrect(RG$G,method='normexp')
RG$G-RG$Gb would be more usual.
>> MA<-normalizeBetweenArrays(Rgene$G,method="scale")
method="quantile" would be more usual.
> Is this is fine?
>
> In this case I have three samples which are treated and the other
three
> without treatment. I would like to get differentially expressed
genes
> between the treated and untreated. In this scenario what should be
the best
> way to create a desing matrix for my further analysis.
Same considerations apply as for any single-channel microarray. See
the
User's Guide for Affymetrix data for example.
Best wishes
Gordon
> Is the following will
> be fine?
> design <- cbind(tx=c(1,1,0,0,0,ntx=c(0,0,1,1,1))
> Is there anything which I should specifically taken care of in these
type of
> scenario?
>
> Thanks
> --
>
> Regards,
> Abhilash
> Graduate student
> Department of Molecular biology
> IOB
